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This paper examines the use of performative verbs meaning “I beg, I ask” and pragmatic markers meaning “please” in the 6th-century Liber vitae patrum by Gregory of Tours. It discusses the frequency of each verb and the possible factors that may have influenced its selection, such as imitation of previous authors, the social status of the communication agents, the requested things, and any difficulty in fulfilling the request. For example, the fact that the highest frequency was found for quaeso (which was perceived as an archaism already in Cicero’s time) suggests that Gregory followed the model of learned men from the 4th and 5th centuries CE who “resuscitated” this verb after its decline in the 2nd and 3rd centuries CE. The paper also examines other additional devices, such as a formula with digneris, and forms of address. [ABSTRACT FROM AUTHOR]

Expert demonstrations in imitation learning often contain different behavioral modes, e.g., driving modes such as driving on the left, keeping the lane, and driving on the right in the driving tasks. Although most existing multi-modal imitation learning methods allow learning from demonstrations of multiple modes, they have strict constraints on the data of each mode, generally requiring a near data ratio of all modes. Otherwise, it tends to fall into a mode collapse or only learn the data distribution of the mode that has the largest data volume. To address the problem, an algorithm that balances real-fake loss and classification loss by modifying the output of the discriminator, referred to as BAlanced Generative Adversarial Imitation Learning (BAGAIL), is proposed. With this modification, the generator is only rewarded for generating real trajectories with correct modes. BAGAIL is therefore able to deal with imbalanced expert demonstrations and carry out efficient learning for each mode. The learning process of BAGAIL is divided into a pre-training stage and an imitation learning stage. During the pre-training stage, BAGAIL initializes the generator parameters by means of conditional Behavioral Cloning, laying the foundation for the direction of parameter optimization. During the imitation learning stage, BAGAIL optimizes the parameters by using the adversary between the generator and the modified discriminator so that the finally obtained policy can successfully learn the distribution of imbalanced expert data. The experiments showed that BAGAIL accurately distinguished different behavioral modes with imbalanced demonstrations. What is more, the learning result of each mode is close to the expert standard and more stable than other multi-modal imitation learning methods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The purpose of this paper is to offer a new coding system to capture preschool playful behaviours based on the imitative, exploratory and imaginative aspects underlying playful behaviours (CIEIPO checklist: Imitation, Exploration, Imagination, for Play Observation). A series of focus group sessions (four in total) involving experts in the field were conducted to identify the most typical preschool play behaviours. In addition, a thorough literature review allowed for the operational definition of the items. The number of participants consisted of 280 preschool-aged children, aged 3 to 5 years (Mage = 4.5, SDage = 1.8), 130 of whom were girls. The most frequently observed behaviours were exploratory (150 times) and imaginative (136 times), while imitative behaviours occurred 58 times. The index of agreement between raters was 0.89 (Cohen's Kappa). The results show important implications for promoting play skills in preschool children, with particular relevance to the developmental functions involved (exploratory, symbolic and imitative skills). [ABSTRACT FROM AUTHOR]

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

This paper attempts to develop a constructive dialogue between moral bioenhancement and Reformed theology of sanctification. According to Reformed theology, human beings are first sanctified by God objectively (passive sanctification) and consequently seek subjectively for their own growth in moral life (active sanctification). Moral bioenhancement and sanctification, thus, share a commonality, that is, emphasizing moral betterment. As such, to the extent that passive sanctification is not obliterated but rather prioritized, moral bioenhancement can be viewed as a consequence of a good work performed freely by the sanctified person to seek for moral growth in the imitation of Christ. [ABSTRACT FROM AUTHOR]

Volumetric representation is a technique used to express 3D objects in various fields, such as medical applications. On the other hand, tomography images for reconstructing volumetric data have limited utilization because they contain personal information. Existing GAN-based medical image generation techniques can produce virtual tomographic images for volume reconstruction while preserving the patient's privacy. Nevertheless, these images often do not consider vertical correlations between the adjacent slices, leading to erroneous results in 3D reconstruction. Furthermore, while volume generation techniques have been introduced, they often focus on surface modeling, making it challenging to represent the internal anatomical features accurately. This paper proposes volumetric imitation GAN (VI-GAN), which imitates a human anatomical model to generate volumetric data. The primary goal of this model is to capture the attributes and 3D structure, including the external shape, internal slices, and the relationship between the vertical slices of the human anatomical model. The proposed network consists of a generator for feature extraction and up-sampling based on a 3D U-Net and ResNet structure and a 3D-convolution-based LFFB (local feature fusion block). In addition, a discriminator utilizes 3D convolution to evaluate the authenticity of the generated volume compared to the ground truth. VI-GAN also devises reconstruction loss, including feature and similarity losses, to converge the generated volumetric data into a human anatomical model. In this experiment, the CT data of 234 people were used to assess the reliability of the results. When using volume evaluation metrics to measure similarity, VI-GAN generated a volume that realistically represented the human anatomical model compared to existing volume generation methods. [ABSTRACT FROM AUTHOR]

Mass panics can arise in response to a variety of situations, such as the spread of pathogens, bank failures, or insecurities about economic supplies. Such panics can produce contagious behaviors such as fleeing social contacts, bank withdrawals, and panic buying. In such situations, the processing of external stimuli, mediated by the perceptions and biases of the individual, can reach a threshold point at which panic behaviors are triggered. Due to the human propensity to imitate the behavior of others in uncertain crisis situations, one individual's panic behavior can spread contagiously. This paper looks at the similarities among case studies of mass panic around the world and from these cases synthesizes a conceptual model to aid our understanding. Decision-makers can use this model to strengthen national resilience against panic-generated behaviors and ensure an orderly and successful public response to future biological, financial, or economic crises. [ABSTRACT FROM AUTHOR]

Generating good and human-like locomotion or other legged motions for bipedal robots has always been challenging. One of the emerging solutions to this challenge is to use imitation learning. The sources for imitation are mostly state-only demonstrations, so using state-of-the-art Generative Adversarial Imitation Learning (GAIL) with Imitation from Observation (IfO) ability will be an ideal framework to use in solving this problem. However, it is often difficult to allow new or complicated movements as the common sources for these frameworks are either expensive to set up or hard to produce satisfactory results without computationally expensive preprocessing, due to accuracy problems. Inspired by how people learn advanced knowledge after acquiring a basic understanding of specific subjects, this paper proposes a Motion capture-aided Video Imitation (MoVI) learning framework based on Adversarial Motion Priors (AMP) by combining motion capture data of primary actions like walking with video clips of target motion like running, aiming to create smooth and natural imitation results of the target motion. This framework is able to produce various human-like locomotion by taking the most common and abundant motion capture data with any video clips of motion without the need for expensive datasets or sophisticated preprocessing. [ABSTRACT FROM AUTHOR]

Roleplay, as a form of speaker imitation, has commonly been used as a tool to investigate the emergence of sociolinguistic expectations in children. In this paper, we integrate previous methodological insights on roleplay with the aim to draft a unified protocol for its design and analysis in (developmental) (socio)linguistics. Special attention is paid to guiding principles for (1) role selection, (2) roleplay elicitation, (3) roleplay identification, (4) isolation of the linguistic variable and (5) cross-verification of the results. The roleplay protocol is applied to a case study on English insertions in Belgian Dutch by five preadolescents, where it seems to effectively capture sociolinguistic expectations: respondents increasingly insert English elements in their performances of English-oriented roles (e.g. rapper) and limit those elements in their performances of Dutch-oriented roles (e.g. farmer). Overall, this paper unites previous insights on the implementation of roleplay designs, aiming to further empirical investigations into speaker imitation in developmental sociolinguistics and the study of linguistic behavior in roleplay in general. • A unified protocol for roleplay design and analysis with children is proposed. • The protocol is created to optimally capture sociolinguistic expectations. • The protocol is applied to a case study on English insertions in Belgian Dutch. • Children use more English insertions for roles like rapper and soccer player. • Children limit their English insertions for roles like farmer and prime minister. [ABSTRACT FROM AUTHOR]

Humans tend to spontaneously imitate others' behavior, even when detrimental to the task at hand. The action observation network (AON) is consistently recruited during imitative tasks. However, whether automatic imitation is mediated by cortico-cortical projections from AON regions to the primary motor cortex (M1) remains speculative. Similarly, the potentially dissociable role of AON-to-M1 pathways involving the ventral premotor cortex (PMv) or supplementary motor area (SMA) in automatic imitation is unclear. Here, we used cortico-cortical paired associative stimulation (ccPAS) to enhance or hinder effective connectivity in PMv-to-M1 and SMA-to-M1 pathways via Hebbian spike-timing-dependent plasticity (STDP) to test their functional relevance to automatic and voluntary motor imitation. ccPAS affected behavior under competition between task rules and prepotent visuomotor associations underpinning automatic imitation. Critically, we found dissociable effects of manipulating the strength of the two pathways. While strengthening PMv-to-M1 projections enhanced automatic imitation, weakening them hindered it. On the other hand, strengthening SMA-to-M1 projections reduced automatic imitation but also reduced interference from task-irrelevant cues during voluntary imitation. Our study demonstrates that driving Hebbian STDP in AON-to-M1 projections induces opposite effects on automatic imitation that depend on the targeted pathway. Our results provide direct causal evidence of the functional role of PMv-to-M1 projections for automatic imitation, seemingly involved in spontaneously mirroring observed actions and facilitating the tendency to imitate them. Moreover, our findings support the notion that SMA exerts an opposite gating function, controlling M1 to prevent overt motor behavior when inadequate to the context. [ABSTRACT FROM AUTHOR]

The aim of this research is to explore emotional processes occurring during educational dialogues on civic and social issues (EDCSI) by asking what factors arouse emotions in EDCSI, how do these factors interact, how do they affect the participants, and how this effect can be explained from the perspective of group therapy. EDCSI involves a complex set of emotions at the individual, inter-personal, and group levels that cannot only be explained by already existing frameworks used in educational research. Thirty-three students discussed civic and social issues using digital media in two different settings: a three-day learning seminar for secondary school students and an undergraduate university course. Using a cued retrospective reporting protocol, the students were interviewed and asked to refer to their overall experience in the discussions and to emotional moments they experienced. The analysis of the interviews shows that factors that arouse emotions pertain to the personal, interpersonal, and group dimensions, and often interact with each other. The emotional processes described by the participants were consistent with factors identified in the field of group psychotherapy such as instillation of hope, universality, imitative behaviors, and interpersonal learning. We therefore claim that research about emotional processes in group therapy may contribute to understanding the multi-level emotional processes occurring in EDCSI and that psychotherapy practices may inspire educators in designing and facilitating EDCSI. [ABSTRACT FROM AUTHOR]

Overimitation — the copying of another’s unnecessary or irrelevant actions toward a goal — is largely considered to be uniquely human. Recent studies, however, have found evidence of this behavior in dogs. Humans seem to overimitate more or less depending on social factors, such as the cultural origin of the demonstrator. Like humans, dogs may have social motivations behind their overimitation, since they have been shown to copy irrelevant actions more from their caregivers than from strangers. By using priming methodology, this study aimed to investigate whether dogs’ overimitation can be facilitated via the experimental manipulation of their attachment-based motivations. To test this, we invited caregivers to demonstrate goal-irrelevant and relevant actions to their dog, following either a dog-caregiver relationship prime, a dog-caregiver attention prime, or no prime. Our results showed no significant main effect of priming on copying behavior for either relevant or irrelevant actions, but we found a trend that unprimed dogs copied the least actions overall. Additionally, dogs copied their caregiver’s relevant actions more often and more faithfully as the number of trials increased. Our final finding was that dogs were much more likely to copy irrelevant actions after (rather than before) already achieving the goal. This study discusses the social motivations behind dog imitative behavior, and has potential methodological implications regarding the influence of priming on dog behavioral studies. [ABSTRACT FROM AUTHOR]

We develop a new classification method for synoptic circulation patterns with the aim to extend the evaluation routine for climate simulations. This classification is applicable to any region of the globe of any size given the reference data. Its unique novelty is the use of the modified structural similarity index metric (SSIM) instead of traditional distance metrics for cluster building. This classification method combines two classical clustering algorithms used iteratively, hierarchical agglomerative clustering (HAC) and k -medoids, with only one pre-set parameter – the threshold on the similarity between two synoptic patterns expressed as the structural similarity index measure (SSIM). This threshold is set by the user to imitate the human perception of the similarity between two images (similar structure, luminance, and contrast), whereby the number of final classes is defined automatically. We apply the SSIM-based classification method to the geopotential height at the pressure level of 500 hPa from the ERA-Interim reanalysis data for 1979–2018 and demonstrate that the built classes are (1) consistent with the changes in the input parameter, (2) well-separated, (3) spatially stable, (4) temporally stable, and (5) physically meaningful. We demonstrate an exemplary application of the synoptic circulation classes obtained with the new classification method for evaluating Coupled Model Intercomparison Project Phase 6 (CMIP6) historical climate simulations and an alternative reanalysis (for comparison purposes): output fields of CMIP6 simulations (and of the alternative reanalysis) are assigned to the classes and the Jensen–Shannon distance is computed for the match in frequency, transition, and duration probabilities of these classes. We propose using this distance metric to supplement a set of commonly used metrics for model evaluation. [ABSTRACT FROM AUTHOR]

A computational human brain model with the voxel-wise assimilation method was established based on individual structural and functional imaging data. We found that the more similar the brain model is to the biological counterpart in both scale and architecture, the more similarity was found between the assimilated model and the biological brain both in resting states and during tasks by quantitative metrics. The hypothesis that resting state activity reflects internal body states was validated by the interoceptive circuit's capability to enhance the similarity between the simulation model and the biological brain. We identified that the removal of connections from the primary visual cortex (V1) to downstream visual pathways significantly decreased the similarity at the hippocampus between the model and its biological counterpart, despite a slight influence on the whole brain. In conclusion, the model and methodology present a solid quantitative framework for a digital twin brain for discovering the relationship between brain architecture and functions, and for digitally trying and testing diverse cognitive, medical and lesioning approaches that would otherwise be unfeasible in real subjects. [ABSTRACT FROM AUTHOR]

Lying and truth-telling are conflicting behavioral strategies that pervade much of the lives of social animals and, as such, have always been topics of interest to both biology and philosophy. This age-old conflict is linked to one of the most serious threats facing society today, viz., the collapse of trustworthy sources of information. Here, we revisit this problem in the context of the two-choice sender–receiver game: the sender tosses a coin and reports the supposed outcome to the receiver, who must guess the true outcome of the toss. For the sender, the options are to lie or tell the truth, while for the receiver, the options are to believe or disbelieve the sender's account. We assume that social learning determines the strategy used by players and, in particular, that players tend to imitate successful individuals and thus change their strategies. Using the replicator equation formulation for infinite populations and stochastic simulations for finite populations, we find that when the sender benefits from the receiver's failure, the outcome of the game dynamics depends strongly on the choice of initial strategies. This sensitivity to the initial conditions may reflect the unpredictability of social systems whose members have antagonistic interests. [ABSTRACT FROM AUTHOR]

Facial mimicry is the automatic imitation of the facial affect expressions of others. It serves as an important component of interpersonal communication and affective co-experience. Facial mimicry has so far been measured by Electromyography (EMG), which requires a complex measuring apparatus. Recently, software for measuring facial expressions have become available, but it is still unclear how well it is suited for measuring facial mimicry. This study investigates the comparability of the automated facial coding software Affdex with EMG for measuring facial mimicry. For this purpose, facial mimicry was induced in 33 subjects by presenting naturalistic affect-expressive video sequences (anger, joy). The response of the subjects is measured simultaneously by facial EMG (corrugator supercilii muscle, zygomaticus major muscle) and by Affdex (action units lip corner puller and brow lowerer and affects joy and anger). Subsequently, the correlations between the measurement results of EMG and Affdex were calculated. After the presentation of the joy stimulus, there was an increase in zygomaticus muscle activity (EMG) about 400 ms after stimulus onset and an increase in joy and lip corner puller activity (Affdex) about 1200 ms after stimulus onset. The joy and the lip corner puller activity detected by Affdex correlate significantly with the EMG activity. After presentation of the anger stimulus, corrugator muscle activity (EMG) also increased approximately 400 ms after stimulus onset, whereas anger and brow lowerer activity (Affdex) showed no response. During the entire measurement interval, anger activity and brow lowerer activity (Affdex) did not correlate with corrugator muscle activity (EMG). Using Affdex, the facial mimicry response to a joy stimulus can be measured, but it is detected approximately 800 ms later compared to the EMG. Thus, electromyography remains the tool of choice for studying subtle mimic processes like facial mimicry. [ABSTRACT FROM AUTHOR]